Video surveillance-based facial recognition is used in some locations to confirm identities of people in a monitored environment. However, video surveillance provides challenges. Presence of individuals and their locations need to be identified. This involves processing an image to locate a person. However, processing an image to locate a person is very processing intensive. The higher the resolution, the more data there is to process, and the processing intensity increases. To address these issues, a first stationary, wide-angle, low-resolution camera has been used to capture images to locate individuals. The low-resolution camera captures images that are processed more quickly do to a relatively small amount of data in a low-resolution image. Once an individual is located, that location is provided to a second, higher resolution, motor-driven camera that is able to articulate and acquire a higher resolution image of a located individual. The higher resolution image is then provided to a facial recognition program for recognition processing. However, the higher resolution images typically include a scene of more than just an individual's face, which is noise that must be eliminated or ignored by the facial recognition process.